Path planning method and system for autonomous mobile robots based on cost map layers and recovery levels

The path planning method for AMRs simplifies and stabilizes path planning by using a cost map with activated layers to reflect zone-specific characteristics, reducing unnecessary path changes and improving efficiency in multi-robot environments.

KR102991547B1Active Publication Date: 2026-07-15SYSWIN MOBILITY CO LTD
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Patent Information

Authority / Receiving Office
KR · KR
Patent Type
Patents
Current Assignee / Owner
SYSWIN MOBILITY CO LTD
Filing Date
2026-05-27
Publication Date
2026-07-15

AI Technical Summary

Technical Problem

Existing path planning methods for autonomous mobile robots (AMRs) in industrial environments are complex and unstable due to varying driving zones and dynamic obstacles, leading to unnecessary detours, lane deviations, and path recalculation issues, especially when multiple robots operate simultaneously.

Method used

A path planning method for AMRs that determines driving area types and activates specific layers of a cost map, such as peer robot filter, lane constraint, and movement trajectory layers, forming a merged cost map to search for reference or alternative paths based on zone-specific characteristics, suppressing unnecessary path changes and re-entry.

Benefits of technology

This approach simplifies path planning by reducing complexity and maintaining stability, suppressing unnecessary path changes, and improving operational efficiency in multi-robot environments by reflecting zone-specific driving characteristics and avoiding lane deviations.

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Abstract

The present invention relates to a path planning method for an autonomous mobile robot, comprising: a step of determining a driving area type of the autonomous mobile robot; a step of determining, based on the driving area type, the active state of at least one of a peer robot filter layer, a lane constraint layer, and a movement trajectory layer among a plurality of layers constituting a cost map; a step of forming a merged cost map by reflecting the active layer among the peer robot filter layer, the lane constraint layer, and the movement trajectory layer; a step of searching for a reference path from a starting posture to a target posture based on the cell cost included in the merged cost map; and a step of determining a recovery level corresponding to the driving area type when it is determined that the reference path is not generated or that obstacle avoidance is required for the reference path. The present invention relates to a path planning method for an autonomous mobile robot, comprising the step of determining whether to search for an alternative path or determining the search range of an alternative path according to the recovery level, wherein the recovery level is determined as any one of a first recovery level in which no search for an alternative path is performed, a second recovery level in which an alternative path is searched within an area limited by the merged cost map, and a third recovery level in which an alternative path is searched within a search range wider than the second recovery level.
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